a - colums

b - Colums type

B - data attributes type :

c - Avg

Standard Deviation

Colums types:

D - Min-Max values

max value

min values

Show where we have an missing data

clculate us the whole file (dmc2010.txt)

Corolzation

i- ii- data distubution - resample

we can see that the sum is 0 so we dont have any missing data on this colmus

i.iii - Distrubtion of the column imbalanced - learn methods for deal with missing data Oversampling with SMOTE')

Random Undersampling

A combination of under- and oversampling method using pipeline

Part2-Normalization

Min-Max scale ( Normalization)

Pyhton Min-Max Scale

try to apply on the data frame we working with .

Z-Score ( Standardization)

My - own function to z-score scaler

Pyhton z-score scaler

Decimal Scale

phyton Decimal scale

Equal-Frequency Binning

My Func

With phyton

Equal-Width Binning

My Func

with phyton

phyton will use equal-width biining by default

Smoothing

Simple Moving Average (SMA)

Weighted Moving Average (WMA)

Exponential Moving Average (EMA)

Binning Methods for Data Smoothing

Smoothing by bin means

Smoothing by bin boundaries